SOTAVerified

Semantic Textual Similarity

Semantic textual similarity deals with determining how similar two pieces of texts are. This can take the form of assigning a score from 1 to 5. Related tasks are paraphrase or duplicate identification.

Image source: Learning Semantic Textual Similarity from Conversations

Papers

Showing 20512100 of 2381 papers

TitleStatusHype
Using Summarization to Discover Argument Facets in Online Idealogical Dialog0
An Optimal Quadratic Approach to Monolingual Paraphrase Alignment0
Random Walks and Neural Network Language Models on Knowledge Bases0
Aligning Sentences from Standard Wikipedia to Simple Wikipedia0
So similar and yet incompatible: Toward the automated identification of semantically compatible words0
Reserating the awesometastic: An automatic extension of the WordNet taxonomy for novel terms0
NASARI: a Novel Approach to a Semantically-Aware Representation of Items0
Can Translation Memories afford not to use paraphrasing?0
Texts in, meaning out: neural language models in semantic similarity task for Russian0
Joint Learning of Distributed Representations for Images and Texts0
Feeling is Understanding: From Affective to Semantic Spaces0
From distributional semantics to feature norms: grounding semantic models in human perceptual data0
BitSim: An Algebraic Similarity Measure for Description Logics Concepts0
Short Text Hashing Improved by Integrating Multi-Granularity Topics and TagsCode0
Context-Dependent Translation Selection Using Convolutional Neural Network0
Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning0
Squibs: When the Whole Is Not Greater Than the Combination of Its Parts: A ``Decompositional'' Look at Compositional Distributional Semantics0
Probabilistic Zero-shot Classification with Semantic Rankings0
Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval0
Higher-order Lexical Semantic Models for Non-factoid Answer Reranking0
Learning Composition Models for Phrase EmbeddingsCode0
A web-based tool to Analyze Semantic Similarity Networks0
Word net based Method for Determining Semantic Sentence Similarity through various Word Senses0
Needle in a Haystack: Reducing the Costs of Annotating Rare-Class Instances in Imbalanced Datasets0
LMSim : Computing Domain-specific Semantic Word Similarities Using a Language Modeling Approach0
Using Mined Coreference Chains as a Resource for a Semantic Task0
A Neural Network Approach to Selectional Preference Acquisition0
Semantic Kernels for Semantic Parsing0
Probabilistic Models of Cross-Lingual Semantic Similarity in Context Based on Latent Cross-Lingual Concepts Induced from Comparable Data0
Modeling Interestingness with Deep Neural Networks0
HulTech: A General Purpose System for Cross-Level Semantic Similarity based on Anchor Web Counts0
Contrasting Syntagmatic and Paradigmatic Relations: Insights from Distributional Semantic Models0
Compositional Distributional Semantics Models in Chunk-based Smoothed Tree Kernels0
OPI: Semeval-2014 Task 3 System Description0
RTM-DCU: Referential Translation Machines for Semantic Similarity0
SAIL-GRS: Grammar Induction for Spoken Dialogue Systems using CF-IRF Rule Similarity0
SAIL: Sentiment Analysis using Semantic Similarity and Contrast Features0
NTNU: Measuring Semantic Similarity with Sublexical Feature Representations and Soft Cardinality0
DIT: Summarisation and Semantic Expansion in Evaluating Semantic Similarity0
DLS@CU: Sentence Similarity from Word Alignment0
Building a Semantic Transparency Dataset of Chinese Nominal Compounds: A Practice of Crowdsourcing Methodology0
BUAP: Evaluating Features for Multilingual and Cross-Level Semantic Textual Similarity0
BUAP: Evaluating Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment0
SemantiKLUE: Robust Semantic Similarity at Multiple Levels Using Maximum Weight Matching0
SemEval-2014 Task 10: Multilingual Semantic Textual Similarity0
SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment0
SemEval-2014 Task 3: Cross-Level Semantic Similarity0
Bielefeld SC: Orthonormal Topic Modelling for Grammar Induction0
Duluth : Measuring Cross-Level Semantic Similarity with First and Second Order Dictionary Overlaps0
SimCompass: Using Deep Learning Word Embeddings to Assess Cross-level Similarity0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SMARTRoBERTaDev Pearson Correlation92.8Unverified
2DeBERTa (large)Accuracy92.5Unverified
3SMART-BERTDev Pearson Correlation90Unverified
4MT-DNN-SMARTPearson Correlation0.93Unverified
5StructBERTRoBERTa ensemblePearson Correlation0.93Unverified
6Mnet-SimPearson Correlation0.93Unverified
7XLNet (single model)Pearson Correlation0.93Unverified
8ALBERTPearson Correlation0.93Unverified
9T5-11BPearson Correlation0.93Unverified
10RoBERTaPearson Correlation0.92Unverified
#ModelMetricClaimedVerifiedStatus
1AnglE-UAESpearman Correlation84.54Unverified
2ST5-XXLSpearman Correlation82.63Unverified
3ST5-LargeSpearman Correlation81.83Unverified
4ST5-XLSpearman Correlation81.66Unverified
5ST5-BaseSpearman Correlation81.14Unverified
6MPNet-multilingualSpearman Correlation80.73Unverified
7SGPT-5.8B-nliSpearman Correlation80.53Unverified
8MPNetSpearman Correlation80.28Unverified
9MiniLM-L12Spearman Correlation79.8Unverified
10SimCSE-BERT-supSpearman Correlation79.12Unverified
#ModelMetricClaimedVerifiedStatus
1MT-DNN-SMARTAccuracy93.7Unverified
2ALBERTAccuracy93.4Unverified
3RoBERTa (ensemble)Accuracy92.3Unverified
4BigBirdF191.5Unverified
5StructBERTRoBERTa ensembleAccuracy91.5Unverified
6FLOATER-largeAccuracy91.4Unverified
7SMARTAccuracy91.3Unverified
8RoBERTa-large 355M (MLP quantized vector-wise, fine-tuned)Accuracy91Unverified
9RoBERTa-large 355M + Entailment as Few-shot LearnerF191Unverified
10SpanBERTAccuracy90.9Unverified
#ModelMetricClaimedVerifiedStatus
1PromCSE-RoBERTa-large (0.355B)Spearman Correlation0.82Unverified
2PromptEOL+CSE+LLaMA-30BSpearman Correlation0.82Unverified
3PromptEOL+CSE+OPT-13BSpearman Correlation0.82Unverified
4SimCSE-RoBERTalargeSpearman Correlation0.82Unverified
5PromptEOL+CSE+OPT-2.7BSpearman Correlation0.81Unverified
6SentenceBERTSpearman Correlation0.75Unverified
7SRoBERTa-NLI-baseSpearman Correlation0.74Unverified
8SRoBERTa-NLI-largeSpearman Correlation0.74Unverified
9Dino (STS/̄🦕)Spearman Correlation0.74Unverified
10SBERT-NLI-largeSpearman Correlation0.74Unverified
#ModelMetricClaimedVerifiedStatus
1AnglE-LLaMA-7BSpearman Correlation0.91Unverified
2AnglE-LLaMA-7B-v2Spearman Correlation0.91Unverified
3PromptEOL+CSE+LLaMA-30BSpearman Correlation0.9Unverified
4PromptEOL+CSE+OPT-13BSpearman Correlation0.9Unverified
5PromptEOL+CSE+OPT-2.7BSpearman Correlation0.9Unverified
6PromCSE-RoBERTa-large (0.355B)Spearman Correlation0.89Unverified
7Trans-Encoder-BERT-large-bi (unsup.)Spearman Correlation0.89Unverified
8Trans-Encoder-BERT-large-cross (unsup.)Spearman Correlation0.88Unverified
9Trans-Encoder-RoBERTa-large-cross (unsup.)Spearman Correlation0.88Unverified
10SimCSE-RoBERTa-largeSpearman Correlation0.87Unverified